Users can give a high-level command like "build a CRM and deploy it to Railway." The agent then handles the entire process: writing code, pushing to a repository, deploying it to a live host, and providing a screenshot of the live app back in the chat.
An agent can build a "tweet leaderboard" app, then use a workflow to fetch daily performance data from that app's API. This data is brought back into the chat, where the agent analyzes it to provide strategic marketing insights, creating a closed-loop system for continuous improvement.
Instead of each team member paying for API access, Buzz allows one powerful machine to host a local LLM. The team can then connect to and share this single compute resource, making powerful AI more accessible and affordable for bootstrapped teams.
Buzz positions shared context as its central engine, not just an add-on. Whether an agent is building a project, analyzing data, or participating in a call, it draws from the same persistent conversation history, making it a powerful foundation for all team activities.
Buzz lets you switch the AI model powering an agent (e.g., from Claude to Codex) while retaining the entire chat history. This eliminates the pain of restarting conversations and re-providing context every time a new, better model is released.
Agents in Buzz don't alter local files. They create separate Git work trees to build and test features in parallel, allowing for safe, simultaneous software development. Agents can even push to their own hosted repositories, creating a self-contained ecosystem.
Because Buzz uses the open protocol Noster, which is tightly coupled with Bitcoin's Lightning Network, it has a built-in pathway for native crypto payments. This could enable frictionless micro-transactions for agents paying for compute or users tipping each other.